Introduction

The central government and the State Council of China highly value the profound impact of artificial intelligence (AI) on education. General Secretary Xi Jinping has emphasized the need to implement the national education digitalization strategy, strengthen the national smart education public service platform, explore effective ways to empower personalized and innovative teaching through digital means, and expand access to quality educational resources. In April 2026, the Ministry of Education and four other departments jointly issued the “AI + Education Action Plan,” providing historic opportunities for the quality and balanced development of education in ethnic regions.

Focus on Unique Needs: Deepening AI Empowerment in All Educational Scenarios

Students in ethnic regions have unique cognitive foundations, language environments, and learning habits, leading to significant differences in learning conditions. It is crucial to integrate AI into the entire educational process to accurately respond to the personalized and differentiated needs of teachers and students. In terms of value guidance, it is important to develop and utilize ideological models and scenario-based intelligent applications to incorporate core content such as education on the awareness of the Chinese national community, the inheritance and development of excellent traditional culture, and the promotion of the national common language into immersive smart education products, making abstract theories tangible. By combining red resources and examples of ethnic unity and progress, a specialized ideological education resource library can be built, achieving alignment between knowledge cultivation and value shaping, thus constructing a shared spiritual home for the Chinese nation.

In terms of precise assistance in learning, intelligent companions equipped with situational guidance and cultural adaptation functions can be utilized to accurately capture students’ cognitive characteristics using knowledge graphs and emotional computing technologies. This allows for real-time monitoring of knowledge consolidation points and weaknesses, creating personalized and progressive learning paths to facilitate large-scale personalized education. For students learning the national common language, features such as voice assessment, intelligent pronunciation correction, and engaging dialogues can enhance language proficiency. In teaching empowerment, an intelligent teaching system can be established to create a closed-loop process of precise lesson preparation before class, dynamic optimization during class, and evidence-based research after class. Before class, intelligent recommendations for teaching resources can lead to efficient lesson preparation; during class, real-time awareness of student dynamics allows for flexible adjustments to teaching strategies; after class, in-depth analysis of teaching behaviors drives reflection and improvement. This closed-loop significantly enhances classroom quality and effectiveness, particularly providing strong teaching support for schools with weak teaching resources.

Enhancing Adaptability: Promoting Comprehensive Optimization of AI-Enabled Educational Resources

The construction of educational resources in ethnic regions has shifted from merely supplementing quantity to enhancing effectiveness. The key lies in breaking down the conversion chain from supply to application, improving the adaptability of resources to teaching scenarios. In terms of resource supply, it is important to develop specialized, localized, and multimodal digital resources based on the key educational needs of ethnic regions. Localities are encouraged to build regional educational corpora, utilizing the national smart education platform for content adaptation, localization of cases, and dynamic updates to achieve precise matching of educational resources with teaching scenarios.

In resource allocation, priority should be given to deploying high-speed networks and edge computing nodes in border pastoral areas, national border schools, remote teaching points, and boarding schools to strengthen the foundation for resource circulation. By leveraging provincial-level intelligent bases to break down data barriers between platforms, resource integration and scheduling can be enhanced, ensuring that quality resources are accessible, operational, and comprehensive. Establishing intelligent channels for educational resource support between eastern and western regions can facilitate targeted delivery and localized adaptation of quality resources. In resource application, the national smart education platform should be utilized to establish a dynamic monitoring and feedback mechanism for resource operation and usage. Based on teacher application data, resource usage preferences, and student engagement metrics, layered analyses can be conducted considering the differences in educational stages, subjects, and regions in ethnic areas, continuously optimizing intelligent recommendation and push strategies to enhance the effectiveness of resource application in teaching scenarios. For some teachers facing difficulties in using digital resources, expert guidance teams can conduct case promotions and on-site guidance to ensure that quality resources are truly understandable, usable, and effective.

Focusing on Competency Enhancement: Strengthening AI Support for the Teaching Workforce

Teachers are the primary resource for high-quality educational development. Improving the quality of education in ethnic regions hinges on enhancing teachers’ intelligent literacy and teaching competence. In terms of training systems, differentiated training should be implemented, with key teachers focusing on the development and application of intelligent teaching tools, young teachers strengthening data-driven learning analysis and precise teaching, and other teachers emphasizing basic applications and concept updates. Building strong county-level “smart education master studios” can play a demonstrative role, encouraging young teachers to lead older ones, promoting a shift from “being able to use” to “willing to use and skilled in using” technology among teachers. An integrated online and offline training platform should be established, combining school-based cases for practical exercises, promoting the “National Training Program” to provide precise support for the construction of the teaching workforce in ethnic regions, and incorporating AI into the curriculum of teacher training colleges in these areas to solidify the foundation of the workforce from the source.

In terms of research mechanisms, an intelligent platform for professional development of teachers in ethnic regions should be constructed. By analyzing classroom teaching behavior data, personalized research suggestions can be generated for teachers, forming an integrated model of “teaching, learning, research, and evaluation”. Support should be provided for the establishment of networked research communities across schools and regions to gradually narrow the research gap. Regular workshops and teaching competitions focused on AI teaching applications should be organized, with award-winning lesson cases promoted through the national smart education platform. In terms of incentive evaluation, intelligent literacy and teaching application effectiveness should be incorporated into the teacher assessment system, with special incentives and project funding established for teachers who excel in AI education and teaching, ensuring preferential treatment in title evaluations and awards, thus fostering a positive environment of “promoting learning through use and excellence through evaluation”.

Promoting Continuity Across All Educational Stages: Building an AI-Enabled Talent Cultivation System in Ethnic Regions

The cultivation of AI literacy needs to permeate the entire talent development process, establishing a vertically integrated and horizontally connected education system for AI across all educational stages and general education for society. In terms of vertical integration, a “General Education Guide for AI in Primary and Secondary Schools” tailored to the realities of ethnic regions can be established during the basic education stage, setting gradient goals by educational stage and using project-based learning and gamified courses to stimulate students’ AI literacy. In higher education, AI should be promoted as a public foundational course in colleges in ethnic regions, facilitating the interdisciplinary integration of AI with特色优势学科. In vocational education, traditional specialties should be upgraded with intelligent technology, and order-based training should be conducted. An integrated cultivation approach across all educational levels, from preschool to higher education, should be promoted, effectively utilizing student digital files to provide personalized learning path planning. AI should be incorporated into lifelong learning systems, creating a ubiquitous learning environment that combines online and offline methods.

In terms of horizontal integration, the collaborative education mechanism among families, schools, and communities should be deepened, extending AI literacy education to family enlightenment and community spaces. General education courses on AI for parents should be developed, expanding coverage through community learning centers and senior universities. Quality educational resources from ethnic region colleges should be opened to society, promoting deep integration of education among schools, families, and communities. The collaborative education between industry, academia, and research should be advanced, focusing on the local industrial needs of ethnic regions such as smart agriculture and特色文旅, building practical training bases for AI integration in education, and supporting leading enterprises to co-build industry colleges with ethnic region schools, relying on industry-education integration models to create a “industry-position-course” map, effectively linking talent cultivation with industrial development.

Strengthening All-Factor Interaction: Promoting Systemic Reform in Education Governance Through AI Empowerment

The modernization level of education governance in ethnic regions directly affects the overall effectiveness of AI empowerment in education. It is necessary to focus on strengthening policy coordination, resource adaptation, and condition guarantees while emphasizing the construction of intelligent centers, monitoring and early warning systems, and collaborative safety guarantees. In terms of intelligent center construction, relying on the national education big data center, a regional education intelligent brain should be established, integrating data aggregation, decision support, policy push, and demand response. A cross-departmental and cross-level data sharing mechanism should be established to ensure precise policy transmission and timely feedback on execution, enhancing the responsiveness and execution effectiveness of educational policies in ethnic regions. Conditional regions should be supported to take the lead in trials, with priority given to deploying intelligent data collection terminals in boarding schools and central schools in towns, exploring a smart service model of “one screen overview, one network handling”.

In monitoring and early warning, big data intelligent monitoring technology should be utilized to dynamically perceive risks such as ideological safety, campus safety, and school dropout risks, constructing a multidimensional early warning indicator system covering teaching quality, teacher mobility, resource allocation, and student development. An intelligent early warning and closed-loop feedback system should be established to enable early detection, prevention, and assistance for risks, providing scientific evidence for precise governance. In terms of safety guarantees, the principle of “intelligence for good” should be adhered to, ensuring the safety of content, data, and algorithms, improving assessment and filing, technical monitoring, risk warning, and emergency response mechanisms, and strengthening the security protection of educational data throughout its lifecycle to effectively prevent issues such as algorithmic discrimination, privacy leakage, and exam-oriented education, ensuring that AI applications operate within a regulated, trustworthy, and benevolent framework.

Empowering education in ethnic regions through AI is a long-term systematic project that requires a unified national approach. Only by adhering to a problem-oriented and application-driven strategy, while promoting the collaborative efforts of technology, resources, talent, and governance through innovative practices, can we effectively transform AI into a significant driver for quality and balanced educational development in ethnic regions, laying a solid foundation for building a strong educational nation and promoting ethnic unity and progress.